activity
20212024
most citedStructure evolution of nanoparticulate Fe2O3

65 citations · 245 across the 9 of their papers we have counts for

collaborators

9 papers

cond-mat.mtrl-sci2024★ 1 cited

Phase stability determination of negative thermal expansion silicates by theory and experiment

Andreas Erlebach, Ghada Belhadj Hassine, Christian Thieme +3

Materials that exhibit zero thermal expansion have numerous applications, ranging from everyday ceramic hobs to telescope mirrors to devices in optics and micromechanics. These mat…

cond-mat.mtrl-sci2024★ 4 cited

Thermomechanical properties of zero thermal expansion materials from theory and experiments

Andreas Erlebach, Christian Thieme, Carolin Müller +4

Origin and composition dependence of the anisotropic thermomechanical properties are elucidated for Ba1-xSrxZn2Si2O7 (BZS) solid solutions. The high-temperature phase of BZS shows…

cond-mat.mtrl-sci2024★ 2 cited

Structure and crystallization of SiO2 and B2O3 doped lithium disilicate glasses from theory and experiment

Andreas Erlebach, Katrin Thieme, Marek Sierka +1

Solid solutions of SiO2 and B2O3 in Li2O 2SiO2 are synthesized and characterized for the first time. Their structure and crystallization mechanisms are investigated employing a com…

cond-mat.soft2024★ 18 cited

Thermodynamic compatibility of actives encapsulated into PEG-PLA nanoparticles: In Silico predictions and experimental verification

Andreas Erlebach, Timm Ott, Christoph Otzen +4

Achieving optimal solubility of active substances in polymeric carriers is of fundamental importance for a number of industrial applications, including targeted drug delivery withi…

cond-mat.mtrl-sci2024★ 65 cited

Structure evolution of nanoparticulate Fe2O3

Andreas Erlebach, Heinz-Dieter Kurland, Janet Grabow +2

The atomic structure and properties of nanoparticulate Fe2O3 are characterized starting from its smallest Fe2O3 building unit through (Fe2O3)n clusters to nanometer-sized Fe2O3 par…

cond-mat.mtrl-sci2024★ 47 cited

Structure and magnetic properties of (Fe2O3)n clusters (n = 1-5)

Andreas Erlebach, Carolin Hühn, Richard Jana +1

Global minimum structures of neutral (Fe2O3)n clusters with n = 1-5 were determined employing the genetic algorithm in combination with ab initio parameterized interatomic potentia…

cond-mat.mtrl-sci2023★ 44 cited

A reactive neural network framework for water-loaded acidic zeolites

Andreas Erlebach, Martin Šípka, Indranil Saha +3

Under operating conditions, the dynamics of water and ions confined within protonic aluminosilicate zeolite micropores are responsible for many of their properties, including hydro…

physics.chem-ph2022

Understanding chemical reactions via variational autoencoder and atomic representations

Martin Šípka, Andreas Erlebach, Lukáš Grajciar

On the time scales accessible to atomistic numerical modelling, chemical reactions are considered rare events. Atomistic simulations are typically biased along a low-dimensional re…

cond-mat.mtrl-sci2021★ 64 cited

Accurate large-scale simulations of siliceous zeolites by neural network potentials

Andreas Erlebach, Petr Nachtigall, Lukáš Grajciar

The computational discovery and design of zeolites is a crucial part of the chemical industry. Finding highly accurate while computationally feasible protocol for identification of…